Six sigma very basic concise explanation and use of it
Skorkovský
KPH_ESF_MU BRNO_Czech Republic

Six Sigma method
•Motorola 1985
•Use in order to produce better products nad less problem processes •PPM- parts per million ->4,4
defects /million opportunities
•Six-Sigma-DMAIC methodology

Where Six Sigma method can be applied



Normal distribution
 Normal distribution curve that illustrates standard deviations. Each band has 1 standard
deviation, and the labels indicate the approximate proportion of area (note: these add up to 99.8%,
and not 100% due to rounding for presentation.)

[USEMAP]


SIX SIGMA Statistical background
Target = m
Some Key measure
Resource : Pro-Enbis

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/
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3
s

Statistical background
Target = m
‘Control’ limits

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3
s

L
S
L
U
S
L
Statistical background
Required Tolerance
Target = m
Lower specification level
Upper specification level

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3
s
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6
s
L
S
L
U
S
L
Statistical background
Tolerance
Target = m
Six-Sigma

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-

3
s
+
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-

6
s
L
S
L
U
S
L
p
p
m
1
3
5
0
p
p
m
1
3
5
0
Statistical background
Tolerance
Target = m
Ppm= parts per million

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/
-

3
s
+
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6
s
L
S
L
U
S
L
p
p
m
0
.
0
0
1
p
p
m
1
3
5
0
p
p
m
1
3
5
0
p
p
m
0
.
0
0
1
Statistical background
Tolerance
Target = m

Statistical background
•
• Six-Sigma allows for un-foreseen ‘problems’ and longer term issues when calculating failure error
or re-work rates
•Allows for a process ‘shift’ (1,5 σ)

L
S
L
0

p
p
m
p
p
m
3
.
4
1
.
5
s
U
S
L
p
p
m
3
.
4
p
p
m
6
6
8
0
3
m
+
/
-

6
s
Statistical background
Tolerance

Performance Standards
2
3
4
5
6
308537
66807
6210
233
3.4
s
PPM
69.1%
93.3%
99.38%
99.977%
99.9997%
Yield
Process
performance
Defects per
million
Long term
yield
Pětiúhelník: Current standard
Current standard
Pětiúhelník: World Class
World Class